Major Take-Aways From This Episode:

My conversation with Greg is a refreshing perspective on innovation largely because of his concept of an innovation matrix. This is a framework that he created to help companies frame problems so that they can find the approach that will most likely solve them.

I love the concept of “looking for problems to solve” versus just generating ideas. I always appreciate the “mental judo” that innovative thinking offers and my conversation with Greg does that. It sort of breaks off the mental cobwebs.

Innovation Labs – While reviewing the episode transcript, I liked what Greg said about innovation labs:

“When an innovation lab is targeted at finding new problems for solutions that exist within the organization, they tend to do pretty well.”

Destructive innovation myths. Innovation just doesn’t happen because someone comes up with one big idea.

Digital Age innovation is different than previous generations. We need to learn how to use new tools properly.

In the resource links you can find a free chapter download Greg has made available along with a video about the book and the Amazon link to buy it.

About Greg Satell

Greg Satell is a popular writer, speaker and innovation advisor, whose work has appeared in Harvard Business Review, Forbes and other A-list publications.

Previously, he served as Senior Vice President Strategy & Innovation at Moxie Interactive, a division of Publicis Groupe, one of the world’s leading marketing services organizations as well as Co-CEO of KP Media, a leading publisher of magazines and websites in Ukraine, including the newsmagazine Korrespondent and the web portal, Bigmir.

You can find Greg’s blog at DigitalTonto.com and on Twitter @DigitalTonto. His first book, Mapping Innovation, has been published by McGraw-Hill in May.

Bill: Let's talk about yourself and innovation. I want to give our audience a chance to see, how long have you been in this field of innovation, what was the genesis for you, and what has brought you to the point you're at today?

[00:00:30]
Greg:

[00:01:00]
Well, I guess the genesis of it is when what you're doing blows up, you have to find something else to do. What I was doing for most of my career was running media companies internationally. I got very good at kind of jumping into new markets, learning the culture, learning the language, and figuring out how to build a business. The reason why I got good at that, what enabled me to do that well, was I built systems for everything, systems for sales, systems for marketing, systems for operations, for editorial. Wherever I went, I could pretty much implement those systems with some modifications, of course.

[00:01:30] The one thing I could never build a system for was innovation, and that always really bothered me, because whenever I had to innovate in my business, which was always, you know there was a lot of good ideas about innovations, [Clayton Christianson 00:01:32] and disruptive innovation and open innovation and design thinking and lean launch pads, and all these things. Whenever you tried to figure something out, it was always someone championing one approach or another, there was never a good framework. I never found one like you have in other fields like marketing or finance.

[00:02:00]

[00:02:30]

[00:03:00] When the country I was living in blew up, and I had to find other things to do, I started talking to pretty much every great innovator I could find, whether that was in a major corporation, in a world-class lab, or at a startup. What I found was, is that innovation is really about solving problems, and there are as many ways to innovate as there are different types of problems to solve. What I did is I built this framework for classifying problems that helped you match the right solution to the right problems, instead of trying to jam any problem you come up against into whatever solution set you had pre-chosen. I also saw that that's where businesses tended to get into a lot of trouble, when they said, "This is the way we innovate," or, "This is our DNA, and we're going to tackle every problem the same way, because Clayton Christianson wrote it, or because that's how we solved the last problem."

You really need to make the solutions fit the problems, so that's what I eventually came up with, and that's what my book's about.

[00:03:30]
Bill:
I'm always curious about this, so you're saying that you can bring some rigor to it via a framework. Is it because serendipity is not as dependable as a framework, or what prompted you to think that you needed to have more structure? When I think of framework, I think of more of a structured process, is that true?

[00:04:00]
Greg:

[00:04:30]
Well, I think there's plenty of structured processes, even disruptive innovation is somewhat of a structured process, lean startup methodologies are a structured process. It wasn't so much bringing more process to it, it's more just the realization that there's a lot of really good ideas about innovation around, they've just never been organized in any particular way. Should you do the Clayton Christianson framework, or should you do what Steve Blank says? I'll give you a really good example.

[00:05:00]

[00:05:30] Recently, Tim Cook, I think it was a year or two ago, he was asked how Apple innovates, and he says, "Well you know, what we really do is we push innovation throughout our organization, and make everybody accountable for creativity and innovation. What you really have to watch out for is assigning some kind of a vice president of innovation, or building some kind of innovation division. Once you do that, you might as well just put a for sale sign on the door." Okay, so you know Tim Cook's a really smart guy, he runs an absolutely fabulous business, tremendously successful, and what he says makes a lot of sense. Then you go across town to Google, and they're piling resources into Google X, which is an innovation division to identify technologies that can be 10 times improvement over what we have now.

[00:06:00]

[00:06:30] Who do you listen to, do you listen to Tim Cook, or do you listen to Google? Or, maybe neither of them, because Apple hasn't had a hit product since 2007, and Google, even longer than that. What do you do? It's really, really confusing, and that's what really drove me to sort of organize it and figure it out, how you can go and listen to people like Tim Cook, who's obviously been very successful, and how you can listen to Google, who's doing the exact opposite of what he says, and still get some use out of it. What became clear is that Google and Apple, they're both attacking very very different types of problems, and then it all makes sense. Well, they're choosing different solutions because they're choosing different problems.

Bill:

[00:07:00] Let's talk about a couple pieces from your book that I thought were really interesting that I wanted you to build upon, and I think this builds upon how people are approaching this from different ways. I think the word, probably, "innovation", might be somewhat, maybe-

Greg: It's become kind of a bad word, it's become synonymous with "impractical" and sort of "quixotic".

Bill:

[00:07:30] Yeah, but I agree with you, and I want you to define it in a moment, but one of the things that I ... Sometimes I think about innovation, is if a customer's willing to pay for something brand new, then you've got something that's innovative, but if it's not, if a customer won't pay you for it, then is that truly innovative? Then I've always had that sort of black and white perspective on it.

Greg: The problem with that type of approach is, I mean it's a perfectly valid approach in some contexts, but then again, that sort of means that Einstein was an innovator, and that just doesn't seem right.

Bill:
[00:08:00]

[00:08:30] Yeah, and you brought that up in the book, because you talked about even with the computer, you kind of reverse engineered, like who were the founding fathers really of the computer? Even all the way back to John Van Newman and [Vanover Bush 00:08:05], and then it's like ideas kept on building upon ideas. Kevin Kelly talks about this as well, it's this really we're building upon thinking from John Van Newman and Vanover Bush to the Mac, and eventually the Alto, all the way through where we are today. When you're in an enterprise, you find that, can someone have innovative thinking that's really just building upon an idea that hasn't made it to market yet?

Greg:

[00:09:00] Yeah, everybody's always building people that come before, I mean everybody's trying to do something new, but you can't do something completely new without building on something that came before, or you're just not going to build anything particularly good. Even like now, we're sort of at a crossroads, because we have Moore's Law blowing up. I mean, Moore's Law is going to end in some people say two years, three years, four years, five years, whatever it is, it's not very long, because there's only so many transistors you can fit onto a silicon wafer before quantum effects start shorting everything out.

[00:09:30]

[00:10:00] There's a bunch of new ideas out there. Some of it has to do with materials like nanotubes or photonics, others have to do with quantum computing. In my book, one of the great joys I had was talking to Charlie Bennett, who helped invent, he's one of the fathers of quantum information, and then you have different ideas like neuromorphic chips or 3D stacking to eliminate the [Von Neumann 00:10:06] bottleneck. There's all these ideas, but even those, when you actually talk to the people who had those ideas, you find that they're actually standing on the shoulders of giants, but just giants in a different field.

[00:10:30]
Bill:
When you say "different field", you mean potentially from a different, outside the computer field, or from a different discipline?

Greg:

[00:11:00]

[00:11:30] Yeah, different discipline, they're sort of crossing domains, and that's how most of the really breakthrough ideas come. There was even a study done recently that most of the really highly cited scientific papers come from a bunch of guys working in a particular field who grabbed one guy working a completely different field who helped them see things in a new way. If you look at neuromorphic chips like the True North chip out of IBM, I talked to the man who led the development of that, and he jumped right in, he talked to neuroscientists, he looked at network theory. An idea always comes from somewhere, you're never starting completely from scratch.

Bill: What do you think is the biggest myth or destructive idea about innovation that you see within organizations right now? What do you see as people being hung up on?

Greg:
[00:12:00]

[00:12:30] I would say there's two. The first is that there's one true path to innovation, and that tends to take you in really bad ways. Usually, people get locked into something because it's been successful in the past, and they get convinced that's the one right way to do it, but eventually, as I like to say, every square business meets its round hole world. Once you get locked into a particular set of strategies because you think that's the one right way to do it, chances are you're opening yourself up to getting disrupted, so you always want to keep a wide lens. The other really I would say harmful myth is that innovation is about ideas, it's about creativity and having ideas, and that is just not true.

[00:13:00] Innovation is not about ideas or how you have them, or divergent thinking, or anything like that. Nobody cares what your ideas are, they care if you can solve problems. One of the things I always advise clients is, "Don't look for a great idea, look for a good problem you can solve."

Bill: I love that. That's really interesting, so it really comes down to ... Okay, building upon the problems, so is it more important to ask a better question?

[00:13:30]
Greg:

[00:14:00]
No, I mean what's "better question"? I hear that a lot too. How do you know what a better question is? At the end of the book, I put in some sort of concluding findings about what great innovators had in common, and the one chief thing I noticed above all is that it wasn't about how they solve problems, it wasn't about how creative they were or how smart they were or whether they were agile, or what kind of organization they had, or anything like that. The one thing that every great innovator that I studied, and I looked at dozens, was that they had a systematic and disciplined process for identifying new problems to solve.

[00:14:30]

[00:15:00] Just to give you some examples, so Experian Data Labs, that's its only mission, it doesn't have a PNL, it doesn't have a revenue target, they're just supposed to go to customers and find out what kind of problems they're having with data, and then they try and solve them. Usually, they can come back with a prototype within 90 days, and if the client likes the solution, they co-create it, and eventually they make it into a business. That's really become like an engine of growth for Experian. Now you look at IBM, you know IBM is a big, slow, bureaucratic company, not at all the type of organization you'd associate with great innovation. Everybody says, "IBM's a dinosaur, their technology is old," and so on and so forth.

[00:15:30]

[00:16:00] 99% of the people who have ever said that are long, long out of business, because somehow IBM finds a way to continually reinvent itself about once every 20 years. They were a tabulating company, and then they got absolutely disrupted by digital computing, and then they ended up dominating digital computing. Then they got disrupted by micro-computers and PC's, and then they reinvented the PC market. Then they almost went bankrupt again, but they reinvented themselves as a consulting company. Now, they're getting killed by the cloud, because although they're building a cloud business, there's not nearly as much money in cloud as they had in installed solutions, so they're reinventing themselves again, and Watson's a big part of that.

[00:16:30]

[00:17:00] How do they keep doing that? Well, they have this huge research division that's continually looking for new problems to solve, and they also have a tradition that they call Grand Challenges, which is just they're trying to go and solve a problem just to see if it can be solved, just to stretch the organization. The last one was the jeopardy grand challenge, where without any kind of business application in mind, they just wanted to see if they could beat humans at Jeopardy. Now that's become Watson, it's become an engine of growth for their business. You see the difference, I mean Experian is looking for problems they can solve within 90 days. IBM's looking for problems that will take them years or even decades to solve, which is something you can do when you have a research division with more Nobel Prize winners than most countries have.

[00:17:30] The way they approach problems is completely different. The similarity there is that they're constantly looking for new problems to solve.

Bill: If a company, like a legacy organization that knows that it needs to start being innovative, essentially what you're saying is one of the ways to start is by being in front, like making it systematized.

Greg: You have to prepare.

Bill: What's that?

[00:18:00]
Greg:

[00:18:30]

[00:19:00]
Well, you have to prepare. Like I said, every business is a square hole business waiting for its round hole world, so it's much more important to prepare than it is to adapt. Once you adapt, you're already losing, once you find you're adapting. I mean, that's a necessity, once it gets to the point that you have to adapt. I mean, nobody ever talks about Apple adapting to the mobile world, or Google adapting to search engines. Actually, when both companies have had to adapt, they tend to do it quite poorly, I mean both have had a lot of misses when they were playing catch-up. What you really want to do is go out and look for what kind of problem can you solve? If you can keep searching out for new problems to solve, it doesn't mean that you're going to get all of them solved, but as long as you can continually find new problems, one a year, one every five years, depending on how big the problem is, you can pretty much guarantee that your business, that you'll be able to sustain your business.

[00:19:30]

[00:20:00] What you have to watch out for is looking at your business and saying, "Oh, this is great, we have this square peg business, we're building more pegs for more holes better, faster, cheaper," and then one day, waking up and find out that you're getting better and better at a bunch of things that people care less and less about, because that's when you end up getting your business into a ton of trouble. Anybody who's been in business for any length of time has seen that happen. We tend to think, you know like if you look at Intel now, they're in really a bad spot with the shift to graphical processors. Nobody really saw that coming, just some guy said, "Hey, you know if we use graphical processors, we could do artificial intelligence a lot better."

Bill: Machine learning, yeah.

Greg:

[00:20:30]

[00:21:00] Machine learning, artificial intelligence, whatever you want to call it. Nvidia didn't invent that, they were just sort of in the right place at the right time, and there's a lot of other different approaches that might soon eclipse the GPU's, and Nvidia will be in the same position that Intel is now. That happens to everybody, it's unavoidable, because every business to a certain extent, is a series of coin flips. You try and narrow down to a couple of viable options, but at the end of the day, you have to take a chance between one or two or three, or whatever it is. At some point, you're going to be wrong, I mean Intel, they got the coin flips right for 40 years, but it eventually caught up to them.

I think when you talk about innovation, I would more look at it as, "What are we doing to prepare for when our business, when the way we make money now becomes irrelevant?"

[00:21:30]
Bill:
When the way we make money becomes irrelevant, what are we doing now to prepare for that?

Greg:

[00:22:00]

[00:22:30] Yeah, it's going to happen, it happens to every business, no matter how smart or fast or creative you are. Eventually, you're going to miss a trick, everybody does, you know you can't get every coin flip right for the rest of your life, it's just an unreasonable expectation, so what can you do now? It's a lot cheaper to do it now. I mean, that's another myth I would say about innovation, that you have to go out and really swing for the fences, or take big risks. You don't have to take huge risks, you know you just need to make some small bets early, and continually search for new problems. Like I said, they do it all different types of ways, I gave the example of Experian and IBM.

[00:23:00] Google, their 20% time program is really just in some sense, a human-powered search engine for new problems. Steve Jobs didn't look for great ideas, he looked for things that sucked. Music players sucked, "Well, let's go and make them great. Mobile phones, they suck, let's go and make them great." It doesn't really matter how you go about it, just that you make sure that you're continually searching for new problems outside of your current line of business that you can solve.

Bill:

[00:23:30] Do you see this coming from any particular, does this have to come from the top, and I don't mean that in a cliché way that everything has to come from the top, but where do you see the biggest impact being within an organization, from the CFO, COO, VP of sales, and across to the CIO, where are you seeing innovation predominately residing, having the biggest impact within an organization? Not just like the traditional technology companies, but like east coast companies or Central America companies that are substantial, but they need to sort of embrace this more deeply.

[00:24:00]
Greg:

[00:24:30]

[00:25:00]

[00:25:30]
I'd say it really does have to come from the top, because searching isn't very efficient, right? When you're searching for new business models or new technologies or new problems to solve, whatever it is, you know it is kind of a serendipitous process. It averages out to a pretty sure thing in the end, but it's not like an optimization-type of thing like Six Sigma would do well. If you have the view from the top that, "Our job is to make our square peg business ever more efficient," then it's really really going to be hard for that searching to happen, unless the people at the top understand that, "Look, we need a certain amount of inefficiency, we need to go out and search, because that's an investment in the future. We don't know which one of these small bets are going to pay off, but the odds are that, just like you can't get every coin flip right, you're not going to strike out every single time you're at bat."

There's certain companies that really understand that, and there's certain companies that don't, and they say, "No, we just want to make everything we do more efficient," and those are the ones who eventually get stuck in the situation where they're getting better and better at things that people care about less and less.

Bill:
[00:26:00] That's your point about, innovation isn't necessarily innovating on the core to make things more efficient, to your point, that it's actually inventing the new.

Greg:

[00:26:30]

[00:27:00] Well, you know again, let's get back to how you define "innovation", there's lots of different innovations, lots of definitions out there. The way I like to define it is, it's a novel solution to an important problem. Some people call sustaining innovation "incremental innovation", and they're very derisive about it, but that's Moore's Law, Moore's Law is incremental innovation. That's what's powered the digital revolution, most of your value is going to come from incremental innovations. The formula that Google and other people use, and that I write about in my book is 70-20-10, where 70% should go towards sustaining innovations, 20% towards adjacencies, and 10% of resources to kind of blue sky opportunities.

[00:27:30]

[00:28:00] As long as you don't take that framework too seriously, it's pretty good, you know those ratios don't have to be exact, but the bulk of your resources should be getting better at doing what you're doing now. Then you also need to set aside some resources for exploring new things, adjacent markets, adjacent capabilities, and also to invent things that haven't been invented yet, even if you can't define either the skills or what the problem is. I think it's more about building up a portfolio of strategies, rather than saying, "This one right here, that's the horse we're going to ride on from now until eternity."

Bill: What is a tool to frame a problem? What do you mean by that? One of the outcomes from the book you mention is that, "Have a tool to frame it." What is that, and why is that important?

Greg:
[00:28:30]

[00:29:00] Well, the main framework in the book is called the innovation matrix, and that is, you just ask two very simple questions: How well is the problem defined, and then how well is the domain defined? What you find is that that tends to break out problems very very well. There's some others that I write about in the book, one is called a three horizons model, where you break things out into existing markets and existing capabilities, and then adjacent markets, adjacent capabilities, new markets, new capabilities. Those are two that I think are very useful.

[00:29:30]

[00:30:00] On a more practical level, two questions that you can use on just a very very granular level: Do we have a technical specification for this, and do we have a job description for this? Once you start asking these questions, you'll see, "Okay, we're dealing with very very different problems, and they require very very different approaches." Then I explain in the book how you can match those different types of problems with solutions best fit to solve them, for instance, problems that are very well-defined, but seem to defy a solution. Those are problems that tend to do pretty well with open innovation strategies, because you need to iterate the solution spaces. Usually what you find is what's very very difficult in one field can be solved very easily in an adjacent field.

[00:30:30] Other times, you have pretty well-defined solutions, but it's not clear what the problem is, so you need to iterate the problem spaces. That's what things like lean startup methodologies and minimal viable products and customer development do really well. You can see business like Uber and AirBnB, they took pretty standard solutions, there was nothing really special about the solution they devised, the genius was that they applied it to a completely new problem, and obviously they built great businesses doing that.

Bill:

[00:31:00] Well, and the funny thing is is that, who had the resources to actually invent this alternative to AirBnB but Hyatt or Marriott, but it didn't come from them, and same thing with Uber, it didn't come from the taxicab industry. Is it necessary to set up your innovation lab, so to speak, outside of the organization, so that it can think independently? What is your thoughts on that?

Greg: Well again, innovation labs have been taking a beating lately.

Bill: Have they?

Greg:

[00:31:30]

[00:32:00] Because so many of them fail, and again, it's about applying them to the right problem. Innovation labs are very good in this disruptive innovation space where you're trying to find new problems for existing solutions. When I was out talking to [Eric Haller 00:31:31] at Experian Labs, I said, "You're not really trying to find solutions for problems, what you're really trying to do is find problems for solutions that you already have," and he said, "Yeah, that's true, I never really thought of it that way." When an innovation lab is targeted at that, at finding new problems for solutions that exist within the organization, they tend to do pretty well. The problem with innovation labs is they're quite often used to go out and solve really hard problems, or as some kind of panacea for innovation as a whole.

When you pick the right solution for the wrong problem, things tend not to go very well. Does that make sense, or have I lost you?

[00:32:30]
Bill:
No, it makes sense, and again, the leaders of Experian have been on the show, and so they have this treasure trove of data that already exists, and they can hunt for-

Greg:

[00:33:00]

[00:33:30] And algorithms, and people with specific skills, they've got great data scientists, so they have a pretty good idea what their capabilities are. What makes it successful is they go out and uncover the problems to solve. Back to your question about Marriott and Hyatt and people like that, there's no reason they should have come up with AirBnB. If you look at AirBnB, what the total market is for, it wouldn't support a business like Marriott or Hyatt, wouldn't even come close. I was looking at the numbers recently, but it's like less than 0.5% of the total hospitality market, so you're talking about these companies with huge shares, so why would they want to do an AirBnB? I mean, it's a great business for a startup and for their investors, I'm not sure it would be such a great business for Marriott, who have much different capabilities.

[00:34:00]

[00:34:30] They know how to, for instance, cater to business travelers. The question for Marriott or Hyatt isn't, "How do we make our own AirBnB?", but, "How can we extend our own assets, our own capabilities, into new markets, or improve them, or to go out and build a new capability that nobody else could ever build?" It's really, I think whenever a new disruptive competitor comes up, they say, "Oh, why didn't somebody see that? Why didn't Marriott see that?" Well, Marriott has no reason to see it.

Bill:

[00:35:00]

[00:35:30] Yeah, they do have no reason to see it, and I think from some of the information and some of the slide decks I see is that AirBnB's valuation is essentially greater than Hyatt's right now, and they have no assets, so they don't own any real estate. Does that mean that Hyatt's business is threatened by AirBnB's? I think that's where it's coming from is, should the hotel industry have innovated there, and kind of transformed themselves? That's frightening probably for the hotel industry, and I mean in my industry, in the technology space, I was meeting with a $100 million company the other day in my own industry, and they're frightened because they're constantly selling hardware and software solutions on premise to large companies, and now these large companies are moving to the cloud, and that's disrupting them.

[00:36:00] The alternative, so they're used to these big hardware/software hits of revenue, and they're frustrated because now they have to invent a new business model that's going to seem not very profitable. You explain manage services to them, and there's not these big cocaine hits of gross profit that hits the bottom line anymore, but they have a choice, they either die or they build a new business model. You could see the fear on their face as they have to approach this and deal with this new reality.

Greg:

[00:36:30]

[00:37:00] Well, that's exactly the problem IBM has now, I mean that's exactly the problem. They built a business on installed solutions, and they've moved to the cloud, but the cloud isn't nearly as profitable as those installed solutions. That's why they're doing things like Watson and quantum computing. The good thing about IBM is with their research division, usually when their business starts failing, they've had something in the cooker for 20 years. Not everybody has that. Watson, I think, the jeopardy grand challenge started, 2004, five or something, I think, and it's just becoming a business now, and they're trying to grow their new businesses as fast as their old ones are dying.

[00:37:30]

[00:38:00] I haven't really looked at the hotel industry in any depth, but I have been looking at the retail industry. It's really interesting, because retailers, they say they're getting killed by e-commerce. Then you look at the numbers and you say, "Okay, well e-commerce as a whole, is I think 8.5% of total retail now," and at the same time, you see all of these e-commerce players building brick and mortar shops. Obviously, retail can't be dead if the e-commerce guys are rushing to get into it, I mean Apple, Amazon, [Bonobos, Warby-Parker 00:37:45]. The real issue is, and again back to this square peg business round peg world thing, is that retail locations historically, their main function has been to drive transactions, and that's how their metrics have been built with sales per square foot, and average transaction, and so on and so forth, and that's what their organizations have been built to solve.

[00:38:30]

[00:39:00] Now the problem has shifted, because transactions can happen anywhere, they can happen on a mobile phone, you know you can buy stuff while you're waiting for your dry cleaning. The function of a retail location has really shifted to being able to learn more about products, to go to a showroom, to be able to ask questions, to get serviced, to upsell, to do all those things. When you look at it in retail, the problem isn't that e-commerce is killing them or anything like that, the problem is they're trying to do what they've done traditionally better and better, where the problem the customer wants solved has completely changed. When you go to a store, you want the high touch, high service experience, you want someone servicing you who really knows what they're talking about, and you're not just being driven to a cash register.

[00:39:30]

[00:40:00]

[00:40:30] I'd say the hotel problem is probably very similar. AirBnB has found another way to solve, "I need a roof over my head," problem. If you're in the hotel business and you're saying, "Oh, our job is to put roofs over people's heads," well, chances are you're not going to make it, because AirBnB can do that much more efficiently than you can, but there's a lot of other things hotels do, like events, like restaurants, like having a concierge there to take care of problems for you. There's lots of things that hotels can do that AirBnB can't. The real challenge I think is to say, "Okay, how can we either build a new capability that nobody else can, or how do we take our existing capabilities and apply them to a new market?"

Bill:

[00:41:00] Right, and one of the pieces that I think I'm hearing a lot as far as new capabilities, which frightens the heck out of people because they don't necessarily, they're inventing something that doesn't necessarily exist, or they can't see it tangibly existing is, you have a part of your book in your process called "leveraging platforms to access ecosystems". I'm trying to give people some carrots here of how they can actually get these initiatives matured within their organizations and build them out. Could you explain a little bit more about how, like what do people do to access talent, resources, ideas, capabilities at pace and at speed? How would you recommend people do that?

[00:41:30]
Greg:

[00:42:00]
Well, I think it's very simple. In my mind, you have to look at technology as extending your own capabilities. These days, because we are so much more connected than we used to be, you really can't compete on your own internal resources alone. I think every single resource, whether it's ... The three pillars are talent, technology, and information. You have to say, "Okay, here are our internal resources, but what platforms can we use to extend those capabilities?" Linux was a great example, where Microsoft said, "Linux is a cancer," but IBM said, "Hey, this is great. We never made money on operating systems anyway. We can just use that to extend and put those resources elsewhere."

[00:42:30]

[00:43:00]

[00:43:30] These days, in terms of talent, there's a number of great platforms. Some of the ones I wrote about in my book were Elance, now UpWork, which is a very, very interesting story. Actually, I want to spend, we don't have much time left, but I want to spend a little bit of time just talking about that in terms of what makes platforms work and not work. Elance started as basically a matching service, very much like Monster.com, to match companies to freelance contractors. They launched it, and it was an absolute disaster, got no traction at all. The investors brought in a new CEO to pursue a completely different business model, which was called "vendor management software".

Bill: Oh, interesting.

Greg:

[00:44:00]

[00:44:30] What they did is they went to a big company like GE and said, "Look, you've got thousands of these contractors running around, you don't have any way of organizing them, what the agreement for work is, what the rates are. Not only have you not organized it, you don't even know what it is, because you've got thousands upon thousands of contracts all over the world. Use this software, and this software will give you visibility and help you manage all those vendors," and it did really, really well. Matter of fact, it did so well, it started to attract the likes of SAP and Oracle into the business. They said, "Well, we're probably not going to survive, because the jig is up," so they ended up selling the business to another company, who was then bought by IBM, I think.

[00:45:00]

[00:45:30] They said, "Hey, let's keep our brand, let's keep some of the intellectual property that we've built, and let's keep some of our best people, and let's go and revisit that original idea, with all that we've learned from the vendor management software, and not just to try and make matches, but also to help make those engagements successful." That combination ended up being obviously a big success, and they built on top of it things like partnerships with training companies, so that they could train and accredit people in new skills. If you're a Flash programmer, and all of the sudden, demand for your services is dropping because of HTML5, you can get trained and certified in HTML5, and still be able to get work.

[00:46:00]

[00:46:30]

[00:47:00] Then that built into new things like companies started coming to them like Microsoft with SharePoint saying, "Hey, we've got this SharePoint thing, we need a bunch of people certified in it so that we sell, and our customers can be confident that they can get their software serviced and designed." They also built things called private clouds. It ended up becoming this whole platform so that companies could access ecosystems of talent, and also the talent could access ecosystems of employers, and that's kind of what a platform does, it helps ecosystems access each other. Very similar thing on the technology side with Open Source. It's very difficult these days to make money on a standard technology. If you look, Silicon Valley has become really an industry that builds applications on top of communal technologies. It's very difficult to find a technology that's not built on Open Source these days, which is why now Microsoft, instead of saying, "Linux is a cancer," they came out a year or so ago saying, "Microsoft loves Linux, we built all of our stuff on top of this."

Also, ecosystems of information, and there's a really interesting company called ... Now I forget their name, oh that's embarrassing.

[00:47:30]
Bill:

[00:48:00]
But I do like the ecosystem, and I completely agree, and it's often not really seen as an option with a lot of the people I'm running into, and you've really got to look at it that way. I have my podcast produced in Czech Republic, I have had material that I needed advanced talent for machine learning and AI for, because I don't carry that native talent within my organization, but my people I work with needed some innovative solutions, and so we just reached out into the ecosystem in this platform that was able to find this talent. Conversely, I could build that ecosystem myself, to extend value upon the services that we're offering. I love this concept, and Linux is a perfect example, as you mentioned, and Elance, now UpWork is, and there's others as well.

Greg:

[00:48:30]

[00:49:00] Yeah, just one more example, now that I remember the name of the company, which is [Bloom Ridge 00:48:22], and they basically have a platform that helps online retailers compete with Amazon. One of the big advantages Amazon has is that they're so big that they have a huge data advantage, but because Bloom Reach powers about 20% of the US e-commerce, they allow more traditional retailers like Toys'R'Us and Crate and Barrel and Neiman Marcus, by pooling their data within the platform, because they all sort of contribute data to their platform, they're able to get that much wider view. When a customer comes to their website, they're not only looking at their data in the context of what they did last time they were on the website, but in the context of the entire platform.

Bill:
[00:49:30] Well, this has been a blast, Greg, and I know that your book is launching very very shortly here, called The Mapping Innovation: A Playbook for Navigating a Disruptive Age. Let's talk about where people can find you online, and where they can find more information about the book, clearly they could go to Amazon, but where can people find you, what's the best place for them to interact with you individually?

Greg:
[00:50:00] The best place is my site, digitaltonto.com, I'm also always accessible through LinkedIn, but if you think I can help your company, just get in touch.

Bill: Right, and this is something you offer through these innovation workshops.

Greg: Yes.

Bill: Of which you talk more clearly and more deeply about your mapping innovation concepts.

Greg: Yeah, it's really a very practical step-by-step process about how to build an innovation playbook and prepare for the future.

[00:50:30]
Bill:
Well Greg, this has been a lot of fun, and I know some of the concepts we're talking about today are fresh, and I love the concepts that you've talked about about problems, finding problems to solve. I think that's really great. Until next time Greg, thank you very much for your time.

As an IT guy, this podcast is a treasure to me. Every individual episode discuss about new security options. Nice source for IT people!

— MattB4SBB from Australia, iTunes

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